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Make Data Work
Oct 15–17, 2014 • New York, NY
Kayur Patel

Kayur Patel
Researcher, Google

Kayur Patel makes data science tools easier to use and studies how people apply machine learning to solve problems and build software. Kayur received his PhD in Computer Science and Engineering from the University of Washington. His graduate work was funded by grants from the NSF and Google as well as the NDSEG and Microsoft Research fellowships. He is currently working at Google and recently taught the Introduction to Data Science course at Columbia.

Sessions

9:00am–5:00pm Wednesday, 10/15/2014
Data Science
Location: 1 E12/1 E13
Fernando Perez (Lawrence Berkeley National Laboratory and UC Berkeley), Brian Granger (Cal Poly San Luis Obispo), Andy Terrel (Bold Metrics), Peter Wang (Continuum Analytics), Jake Vanderplas (eScience Institute, University of Washington), Olivier Grisel (Inria & scikit-learn), Travis Oliphant (Continuum Analytics, Inc.), William McKinney (Cloudera), Trent Nelson (Continuum Analytics), Kayur Patel (Google), Kester Tong (Google)
Average rating: ****.
(4.43, 14 ratings)
Python has become an increasingly important part of the data engineer and analytic tool landscape. Pydata at Strata provides in-depth coverage of the tools and techniques gaining traction with the data audience, including iPython Notebook, NumPy/matplotlib for visualization, SciPy, scikit-learn, and how to scale Python performance, including how to handle large, distributed data sets. Read more.